Gender: Female 
Age: 25-34
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Nothing 
Education: High school or below
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 6
Home: Own 
Employment: Employed part time
Occupation: Technicians and associate professionals (those who apply scientific or artistic concepts and operational methods, e.g. secretaries, fitness workers, lab technicians)
Mother's occupation: Elementary occupations (jobs that involve simple and routine tasks which may require the use of hand-held tools and considerable physical effort)
Father's occupation: Elementary occupations (jobs that involve simple and routine tasks which may require the use of hand-held tools and considerable physical effort)
Hobbies: Listen to rock/indie music;Exercise;Use social media;Go to museums and galleries;Do arts and crafts 
Devices used daily: Laptop;Smartphone;Tablet;Smartwatch 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
NLP tools they would find useful: Sentiment analysis (e.g. automatically detect if user reviews are positive or negative)Machine translation (e.g. translate Chinese or Russian into English, and vice versa) 
Frequency of LLM use: Nearly every day
LLMs used: ChatGPT;Google Gemini;Grok;Microsoft Bing AI 
LLM use cases: Coding;Translation;Writing (e.g., composing emails);Proofreading/Editing (e.g., grammar, spelling, structure improvements);Generate art 
Contexts of LLM use: Work 
Prompt 1: Generate a function to make an element with a class disapear in js
Prompt 2: Create a pseudo function to change position of an element on click of another element in js
Prompt 3: Build a function to remove colon from labels in woocommerce php
Prompt 4: Build a wordpress function to loop posts from a custom post type with a certain tag 
Prompt 5: Create a js function to toggle a button from being disabled
Prompt 6: create a function which reads data from a sql table js
Prompt 7: how to hide a div on click of another element js
Prompt 8: create a function to output custom field wordpress php
Prompt 9: how to loop through a file and output the values comma seperated objective c
Prompt 10: create an intro text about web development for my website